I understand that the batch size is the number of examples you pass into the neural network (NN). If the batch size is 10, it means you feed the NN 10 examples at once.
Assuming I have an NN with a single
Dense layer. This
Dense layer of
20 units has an input shape
(10, 3). This means that I am feeding the NN 10 examples at once, with every example being represented by 3 values. This
Dense layer will have an output shape of
I understand that the 20 in the 2nd dimension comes from the number of units in the
Dense layer. However, what does the
10 (Batch Size) in the first dimension mean? Does this mean that the NN learns 10 separate sets of weights (with each set of weights corresponding to one example, and one set of weights being a matrix of 60 values:3 features x 20 units)?